Articles | Volume 10, issue 12
Nat. Hazards Earth Syst. Sci., 10, 2441–2450, 2010
https://doi.org/10.5194/nhess-10-2441-2010

Special issue: 11th Plinius Conference on Mediterranean Storms

Nat. Hazards Earth Syst. Sci., 10, 2441–2450, 2010
https://doi.org/10.5194/nhess-10-2441-2010

Research article 02 Dec 2010

Research article | 02 Dec 2010

An optimized ensemble sensitivity climatology of Mediterranean intense cyclones

L. Garcies and V. Homar L. Garcies and V. Homar
  • Universitat de les Illes Balears, Dept. Física, Ctra. Valldemossa, km. 7.5, 07122, Palma de Mallorca, Spain

Abstract. A new approach was recently proposed to compute climatological statistical sensitivities. It was applied on an already available classification of Mediterranean intense cyclones. However, those sensitivity results are questionable due to the limited homogeneity of some cyclone classes, which severely hampers the application of the statistical sensitivity analysis technique. In this study, a new classification of Mediterranean intense cyclones is built with the aim of improving the reliability of the final climatological sensitivity results. In addition to implementing a regional classification and a subsequent division according to the preceding conditions that lead to cyclone formation, a cluster pruning is applied to maximize the homogeneity of the classes. The increased cluster homogeneity and the higher significance of the obtained sensitivity estimates are quantified. Furthermore, the improved representativeness of the sensitivity fields derived after cluster pruning is tested and compared to previous results by means of numerical experiments. Eventually, summary sensitivity fields highlight the European Atlantic coasts, central and western Europe, the central and western Mediterranean basin and north african lands as sensitive regions for the evolution of these Mediterranean high-impact systems. Although some outstanding improvements are confirmed in this study, a further verification experiments are needed to objectively verify the sensitivity results and build solid confidence on the method.

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